Text-Matching Software
Gimmick or Godsend?
Jayson MacLean
Graduate Ombudsperson
University of Alberta
Text-Matching Software
Part I - Google for Gogol …
On March 25th there took place, in Petersburg, an extraordinarily strange occurrence. The
barber Ivan Yakovlevich, who lives on Voznesensky Avenue (his family name has been lost and
even on his signboard, where a gentleman is depicted with a lathered cheek and the inscription
“Also bloodletting,” there is nothing else)—the barber Ivan Yakovlevich woke up rather early
and smelled fresh bread. Raising himself slightly in bed he saw his spouse, a rather respectable
lady who was very fond of drinking coffee, take some newly baked loaves out of the oven.
Text-Matching Software
•
On March 25th there took place, in Petersburg, an extraordinarily strange occurrence. The
barber Ivan Yakovlevich, who lives on Voznesensky Avenue (his family name has been lost and
even on his signboard, where a gentleman is depicted with a lathered cheek and the inscription
“Also bloodletting,” there is nothing else)—the barber Ivan Yakovlevich woke up rather early
and smelled fresh bread. Raising himself slightly in bed he saw his spouse, a rather respectable
lady who was very fond of drinking coffee, take some newly baked loaves out of the oven.
• “The Nose”
• Nikolai Gogol, 1809 - 1852
Section 2: What is TMS?
• Text-Matching versus Plagiarism Detection
• How they work:
1.
2.
Content from submitted essay is compared to content from
other sources (websites, journals, essay banks).
Similarities between text in submitted essay and source content
are identified.
• Examples:
•
•
•
•
Turnitin
Ithenticate
Google
In-house programs
Section 2: What is TMS?
• turnitin.com
OriginalityCheck, GradeMark, PeerMark
300 million archieved student papers
24 billion web pages
120 million articles from 110,000 journals, periodicals
and books
• 190,000 papers submitted every day
• 126 countries
• over half of the top 100 U.S. high schools and top 100
U.S. colleges and universities employ turnitin
•
•
•
•
• turnitin.com
• ‘Originality Report’
• highlighted text
• degree of originality
Section 3 – Points in Favour of Using TMS
at Educational Institutions
1. Increase in cases of plagiarism over the past
decades:
• Stats for this
• The Internet allows for quick and easy cutting and
pasting:
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–
–
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personal webpages
online university courses
online encyclopedia, Wikipedia
online sharing of information between students
Section 3 – Points in Favour of Using TMS
at Educational Institutions
2. Efficiency and convenience for grading and
marking:
• systematic approach to scanning documents for copied text
• significant % of plagiarism cases involve use of past course
material
• allows for complete electronic processing of assignments:
–
–
–
–
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electronic submission (with submission time and date)
electronic feedback and comments
peer review
grade tabulation
electronic return to students
Section 3 – Points in Favour of Using TMS
at Educational Institutions
3. Pedagogical function:
• increases awareness of plagiarism and knowledge of
plagiarism
• students can self-check for matching text and ‘originality’
4. Deterrence function:
• Stats
5. Students prefer it:
• convenience of submission, return of assignments
• self-direction and empowerment
• effective in preventing other students from plagiarizing
Section 3 – Points Against Using TMS
at Educational Institutions
1. TMS does not catch all forms of plagiarism:
• from sources not found within database of searchable
content (e.g. from essay mills, from other students)
• Types of Plagiarism!
• non-verbatim plagiarism: unattributed paraphrase
Section 3 – Points Against Using TMS
at Educational Institutions
2. TMS does not do away with the need for
interpretation of results:
• degrees of plagiarism
• student intent
• “under-the-radar” plagiarism
3. TMS changes the student-teacher (or
student-institution) relationship:
• presumed guilty
• further automation of the relationship
• But … research appears to counter this charge
Section 4 – TMS and Educational Institutions
1. TMS use at Canadian universities and
colleges
•
•
•
•
•
McGill, 2004
Mount Saint Vincent, 2006
Dalhousie, 2011
Prevalence of TMS use at Canadian institutions
Prevalence of institution-wide policies on TMS
Section 4 – TMS and Educational Institutions
2. TMS use in the U.S.
•
•
Princeton, 2006
Vanderhye v. iParadigms LLC, 2009
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–
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Alleged infringement of students’ rights under U.S. copyright
law
Court found iParadigms’ use of students’ work to be
covered under “fair use” exception to copyright law
U.S. Copyright Act and the fair use provision
Section 4 – TMS and Educational Institutions
3. Canadian Copyright Act and TMS
•
•
Fair dealings
Consent
4. Canadian Privacy Act and TMS
•
Data storage
Text-Matching Software
Gimmick or Godsend?
• Overview and Discussion